As the most important driving force for ensuring the effective supply of grain in the country, the production stability of the major grain-producing areas directly concerns the national security of China. In this paper, considering the “water–soil–energy–carbon” correlation, water, soil and energy resource factors, and carbon emission constraints were included in an index system, and the global common frontier boundary three-stage super-efficient EBM–GML model was used to measure the grain production resource utilization efficiency of the major grain-producing areas in China from 2000 to 2019. This paper also analyzed the static and dynamic spatiotemporal characteristics and the restrictions of utilization efficiency. The results showed that, under the measurement of the traditional data envelopment analysis model, the grain production resource utilization efficiency in the major producing areas is relatively high, but there is still room to improve by more than 20%, and grain production still has enormous growth potential. After excluding external environmental and random factors, it was found that the utilization efficiency of grain production resources in the major producing areas decreased, and the efficiency and ranking of provinces changed significantly. External factors inhibit pure technical efficiency and expand the scale efficiency. The utilization efficiency of Northeast China was much higher than that of the Huang-Huai-Hai region and the middle and upper reaches of the Yangtze River region, and its grain production resource allocation management had obvious advantages. The total factor productivity index of food production resources showed an upward trend as a whole, and its change was affected by both technological efficiency and technological progress, of which technological progress had the greater impact. Therefore, reducing the differences in the external environment of different regions while making adjustments in accordance with their own potential is an effective way to further improve the utilization efficiency of food production resources.

Increasing agricultural output by reducing capital misallocation is a capital-saving strategy, as it does not require the usage of additional inputs. Based on the panel data of 36 prefecture-level cities in Northeast China from 2011 to 2020, this paper uses the spatial Durbin model to test the impact of capital mismatch on agricultural output and its mechanisms. We found that capital misallocation is prevalent in prefecture-level cities, showing a spatial distribution characteristic of “north-south confrontation and central collapse”, with a significant spatial spillover effect. A one-unit increase in capital misallocation leads to a 16.00% decrease in local agricultural output and a 1.80% decrease in adjacent areas. However, with the optimization and upgrading of the agricultural industry and agricultural technology progress, the inhibitory effect of capital misallocation on the growth of agricultural output is constantly weakening. The above conclusion still holds after a series of robustness tests. The conclusion of this paper provides policy inspiration for promoting the rational allocation of factors between cities and regions, coordinating regional coordinated development, and then promoting the sustainable growth of agricultural output.

Coarse wood debris (CWD) plays a critical role in forest productivity, nutrient cycling, decomposition, and carbon sequestration, and shapes the carbon pool in the forest ecosystem. However, the elemental composition of CWD varies among different forest types and decay classes for the same dominant tree species (Pinus koraiensis, PK). We compared CWD elemental composition across different forest types (Picea koraiensis-Abies nephrolepis-Pinus koraiensis forest (PAPF), Betula costata-Pinus koraiensis forest (BPF), Tilia amurensis-Pinus koraiensis forest (TPF)), considering four classes of wood decay. Results showed that N, P, Mg, Mn, Na, Zn, S, Al, and Fe concentrations almost totally increased with decay level for all three forest types, except for K in all three forest types and B in Picea koraiensis-Abies nephrolepis-Pinus koraiensis forest (PAPF). Similarly, maximum concentrations of N, P, B, Mg, K, C, Zn, and Mn of CWD were observed in Betula costata-Pinus koraiensis forest (BPF) under varying decay classes, but their maximum concentrations of Fe and S were found in Picea koraiensis-Abies nephrolepis-Pinus koraiensis forest (PAPF) and Tilia amurensis-Pinus koraiensis forest(TPF), respectively. Only C content did not significantly differ in decay classes across all three forest types. The C:N ratio decreased significantly with increasing decay levels across all forest types. The decay rates were significantly related to N concentration and C:N ratio in decay classes across all forest types. These results suggest that C and N concentration are the key factors affecting its decomposition. The variation in nutrient concentrations observed here underscores the complexity of nutrients stored in wood debris in forested ecosystems.